GWAF (version 2.2)

geepack.lgst.batch.imputed: function to test genetic associations between a dichotomous trait and a batch of imputed SNPs in families using Generalized Estimation Equation model

Description

Fit logistic regression via Generalized Estimation Equation (GEE) to test associations between a dichotomous phenotype and all imputed SNPs in a genotype file in family data under additive genetic model. Each family is treated as a cluster, with independence working correlation matrix used in the robust variance estimator. This function applies the same trait-SNP association test to all SNPs in the imputed genotype data. The trait-SNP association test is carried out by geepack.lgst.imputed function where the geese function from package geepack is used.

Usage

geepack.lgst.batch.imputed(genfile, phenfile, pedfile, outfile, phen, 
covars = NULL, col.names = T, sep.ped = ",", sep.phe = ",", sep.gen = ",")

Arguments

genfile

a character string naming the genotype file for reading (see format requirement in details)

phenfile

a character string naming the phenotype file for reading (see format requirement in details)

pedfile

a character string naming the pedigree file for reading (see format requirement in details)

outfile

a character string naming the result file for writing

phen

a character string for a phenotype name in phenfile

covars

a character vector for covariates in phenfile

col.names

a logical value indicating whether the output file should contain column names

sep.ped

the field separator character for pedigree file

sep.phe

the field separator character for phenotype file

sep.gen

the field separator character for genotype file

Value

No value is returned. Instead, results are written to outfile.

phen

phenotype name

snp

SNP name

N

the number of individuals in analysis

Nd

the number of individuals in affected sample in analysis

AF

imputed allele frequency of coded allele

AFd

imputed allele frequency of coded allele in affected sample

beta

regression coefficient of SNP covariate

se

standard error of beta

remark

warning or additional information for the analysis, note that the genotype counts are based on rounded imputed genotypes; 'not converged' indicates the GEE analysis did not converge; 'logistic reg' indicates GEE model is replaced by logistic regression; 'exp count<5' 5="" indicates="" any="" expected="" count="" is="" less="" than="" in="" phenotype-genotype="" table;="" 'not="" converged="" and="" exp="" count<5',="" 'logistic="" reg="" &="" count<5'="" are="" noted="" similarly;="" 'collinearity'="" collinearity="" exists="" between="" snp="" some="" covariates<="" dd="">

pval

p-value of the association test based on chi-square statistic

Details

Similar to the details for geepack.lgst.batch but here the SNP data contains imputed genotypes (allele dosages) that are continuous and range from 0 to 2. In addition, the user-specified genetic model argument is not available.

Examples

## Not run: 
# geepack.lgst.batch.imputed(phenfile="simphen.csv",genfile="simgen.csv",
# pedfile="simped.csv",phen="aff",covars="sex",outfile="simout.csv",col.names=T,
# sep.ped=",",sep.phe=",",sep.gen=",")
# ## End(Not run)